title: Bias analysis to improve monitoring an HIV epidemic and its response: approach and application to a survey of female sex workers in Iran.
abstract: BACKGROUND
  We present probabilistic and Bayesian techniques to correct for bias in categorical and numerical measures and empirically apply them to a recent survey of female sex workers (FSW) conducted in Iran.
  
  
  METHODS
  We used bias parameters from a previous validation study to correct estimates of behaviours reported by FSW. Monte-Carlo Sensitivity Analysis and Bayesian bias analysis produced point and simulation intervals (SI).
  
  
  RESULTS
  The apparent and corrected prevalence differed by a minimum of 1% for the number of 'non-condom use sexual acts' (36.8% vs 35.8%) to a maximum of 33% for 'ever associated with a venue to sell sex' (35.5% vs 68.0%). The negative predictive value of the questionnaire for 'history of STI' and 'ever associated with a venue to sell sex' was 36.3% (95% SI 4.2% to 69.1%) and 46.9% (95% SI 6.3% to 79.1%), respectively. Bias-adjusted numerical measures of behaviours increased by 0.1 year for 'age at first sex act for money' to 1.5 for 'number of sexual contacts in last 7 days'.
  
  
  CONCLUSIONS
  The 'true' estimates of most behaviours are considerably higher than those reported and the related SIs are wider than conventional CIs. Our analysis indicates the need for and applicability of bias analysis in surveys, particularly in stigmatised settings.
authors.affiliation: Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, , Tehran, Iran.
authors.forename: Ali
authors.initials: A
authors.lastname: Mirzazadeh
authors.forename: Mohammad-Ali
authors.initials: MA
authors.lastname: Mansournia
authors.forename: Saharnaz
authors.initials: S
authors.lastname: Nedjat
authors.forename: Soodabeh
authors.initials: S
authors.lastname: Navadeh
authors.forename: Willi
authors.initials: W
authors.lastname: McFarland
authors.forename: Ali Akbar
authors.initials: AA
authors.lastname: Haghdoost
authors.forename: Kazem
authors.initials: K
authors.lastname: Mohammad
mesh_terms: D001499:Bayes Theorem; D015982:Bias; D017280:Condoms / Q000706:statistics & numerical data; D005260:Female; D015658:HIV Infections / Q000453:epidemiology*; D006801:Humans; D007407:Interviews as Topic; D007492:Iran / Q000453:epidemiology; D009010:Monte Carlo Method; D015995:Prevalence; D012307:Risk Factors; D012309:Risk-Taking; D060386:Sex Workers; D011795:Surveys and Questionnaires
keywords: AIDS; HEALTH BEHAVIOUR; HIV; MEASUREMENT; RESEARCH METHODS